Rowan Trollope's departure from Cisco in May took many in the industry by surprise. In his five years as a top executive, Trollope was widely credited with reinvigorating Cisco's collaboration portfolio. At the end of his tenure, he made the bold move of merging Cisco's core meeting software, Webex and Spark.
Trollope is now the CEO of cloud contact center vendor Five9, a startup in San Ramon, Calif., with revenue one-twenty-fifth the size of the collaboration division at Cisco. Trollope described his new company as smaller than his old one, but also nimbler.
In an interview this week, Trollope spoke about why he left Cisco and the use cases of the contact center AI he's likely to bring to Five9.
Editor's note: The following was edited for style, clarity and brevity.
How will your leadership change Five9?
Rowan Trollope: I wasn't hired because the company needed a new strategy. The way the search happened was ultimately because the former CEO, unfortunately, had a health issue and couldn't continue. So, it's kind of a different CEO transition in that sense; it's not like the company needed a transformation or a new direction.
I am a different CEO, I think, than the former CEO just in terms of my background. I'm a much more product-focused executive, whereas Mike [Burkland] was more focused on sales and go-to-market. And so, you know, my focus will probably be more on product. I think the innovation side of this story that's unfolding needs a lot of attention.
Cisco is also a big contact center vendor. Why didn't you want to stay there?
Trollope: Timing in business is so important. And the time for a cloud contact center is now. And, you know, I had been at Cisco for five years, very successful with transforming the portfolio and having a good run. But this was an opportunity to join a very special company, a much smaller company, more nimble, and something that I just, personally, was very interested in.
It's not anything negative about Cisco. I enjoyed working there, I learned a lot, it's a great company, and I think their collaboration business has great prospects. But I couldn't say no to this opportunity.
What applications of contact center AI do you think will have the biggest impact on the industry?
Trollope: One, data analytics. All the voice traffic coming through your contact center today is only used for the purposes of quality-assurance checks and compliance. So, the first real big opportunity is to unlock the value of that data.
Speech-to-text, and then natural language understanding to provide analytics on top of that data, can really [help a company] understand at the business level what's going on with my customers [and] what are they asking about. If you look at how call centers work today, at the very end of the call, they will enter a reason code, like install problem or password reset. And that's just so limiting, and the industry has struggled to make sense of this data. That's why I call it 'dark data.'
Two, virtual agents. The technology has just gotten to the point where it could be feasible that when you call into your typical call center, instead of getting, 'Welcome to ABC company. Push one for sales; push two for product,' that you will be greeted by, 'Hi, ABC company, can I help you?' And you say, 'Yeah, I've been having a problem with your product. I'm wondering if I can speak to Joe in support.' 'Oh, sure, yeah, let me get Joe on the line.'
That's not a human; that conversation was with a robot. That's feasible now. It wasn't feasible a year ago. And it will become more and more feasible. So, the death of the IVR [interactive voice response] couldn't come soon enough for most. If you're a consumer, that's like the worst experience ever, right?
Three, agent guidance. If the computer can listen to all of the context of the conversation in real time and present me with advanced search results from my knowledge bases and my company information and my workflows, I become a smarter agent.
Today, the agents will be listening to your call. And they will be sitting with a whole bunch of windows open, and they will be Googling for this, or searching their internal knowledge base for that, or typing a text message to a peer to say, 'Do you know what this problem could be?' And all that can be made much easier through AI. So, that's about assisting agents to get better answers faster.